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Deke, John; Finucane, Mariel; Thal, Daniel – National Center for Education Evaluation and Regional Assistance, 2022
BASIE is a framework for interpreting impact estimates from evaluations. It is an alternative to null hypothesis significance testing. This guide walks researchers through the key steps of applying BASIE, including selecting prior evidence, reporting impact estimates, interpreting impact estimates, and conducting sensitivity analyses. The guide…
Descriptors: Bayesian Statistics, Educational Research, Data Interpretation, Hypothesis Testing
Hicks, Tyler; Rodríguez-Campos, Liliana; Choi, Jeong Hoon – American Journal of Evaluation, 2018
To begin statistical analysis, Bayesians quantify their confidence in modeling hypotheses with priors. A prior describes the probability of a certain modeling hypothesis apart from the data. Bayesians should be able to defend their choice of prior to a skeptical audience. Collaboration between evaluators and stakeholders could make their choices…
Descriptors: Bayesian Statistics, Evaluation Methods, Statistical Analysis, Hypothesis Testing
Klugkist, Irene; Laudy, Olav; Hoijtink, Herbert – Psychological Methods, 2010
In this article, a Bayesian model selection approach is introduced that can select the best of a set of inequality and equality constrained hypotheses for contingency tables. The hypotheses are presented in terms of cell probabilities allowing researchers to test (in)equality constrained hypotheses in a format that is directly related to the data.…
Descriptors: Bayesian Statistics, Models, Selection, Probability
Kuiper, Rebecca M.; Hoijtink, Herbert – Psychological Methods, 2010
This article discusses comparisons of means using exploratory and confirmatory approaches. Three methods are discussed: hypothesis testing, model selection based on information criteria, and Bayesian model selection. Throughout the article, an example is used to illustrate and evaluate the two approaches and the three methods. We demonstrate that…
Descriptors: Models, Testing, Hypothesis Testing, Probability

Seaman, Samuel; And Others – 1984
The probability of obtaining a significant statistic, using the parametric analysis of covariance (ANCOVA) and the rank transform ANCOVA, was estimated for three conditions defined in terms of conditional distributions for two groups. The distributions were both normal, both skewed in the same direction but to different degrees, or both skewed to…
Descriptors: Analysis of Covariance, Correlation, Hypothesis Testing, Probability
Stallings, William M. – 1985
In the educational research literature alpha, the a priori level of significance, and p, the a posteriori probability of obtaining a test statistic of at least a certain value when the null hypothesis is true, are often confused. Explanations for this confusion are offered. Paradoxically, alpha retains a prominent place in textbook discussions of…
Descriptors: Educational Research, Hypothesis Testing, Multivariate Analysis, Probability

Offenbach, Stuart I.; And Others – Child Development, 1984
Examines hypotheses and strategies used by children at the kindergarten, second-, fourth- and sixth-grade levels in making proportional judgements. The task involved 36 trials in which the child had to choose between two groups to obtain a target-color "chip." Results generally conformed to the developmental sequence proposed by Piaget…
Descriptors: Children, Concept Formation, Developmental Stages, Grade 2